1. Field of the Invention
The invention relates to a coding process for original infrared images, wherein the images are converted to negative black and white and wherein specific split colors are added causing a substantial difference in the way the retina and brain process the resultant images. The process allows for improved discrimination and interpretation of thermal content of infrared images and for easier understanding and perceiving of information contained in infrared images. Reading of infrared images coded using the process is much less tiring to the operator of thermal cameras and related software relative to original infrared images.
2. Description of the Related Art
Infrared thermography has been in development for over 50 years and significant advances have been made in the area of sensors, cooling, portability, weight, and ergonomics of infrared apparatus. The main purpose of these developments was to construct infrared apparatus that is more suitable and ergonomic for portable use and applicable to a wider array of applications. However, while much progress has been made in the realm of infrared hardware, visualization of thermal infrared images has largely been left behind and interpreting infrared images still presents a challenge.
Images produced by infrared thermographic equipments are alien to the human brain and cognitive process since our eyes perceives only the visible light range out of the entire electromagnetic spectrum. Chemical processes inside the human eye and functional cells distributions as well as cognitive-perceptual impact of images are a crucial part in the perception, detection, understanding and recording of infrared images. This invention alleviates the challenge of interpreting infrared images by processing raw infrared images so as to make them much more suitable for the human eye and mind.
In general, unprocessed infrared images are produced by infrared cameras, shown in FIG. 1, and described, e.g., in U.S. Pat. Nos. 5,420,419, 6,144,031, and D 483,782, which are designed to detect infrared radiation emitted by any object and transform these information into human-eye-recognizable images, making them possible to be interpreted in any specific situation.
Being so, all images produced by infrared cameras, digital or analog, are detected by an electronic sensor made from tiny cells called pixels, varying from 1 (one) to thousands or even millions, according to the camera capabilities (FIG. 2). After several electronic internal operations, the infrared radiation sensed by these pixels is coded to a matrix (Table 1) that is generated by electronic circuitry (FIG. 3) or other methods. Each value in Table 1 corresponds to incident radiation registered by a specific pixel of the sensor converted to a final value representing the adjusted temperature of the subject. U.S. Pat. No. 5,420,419 to Wood shows an example of an infrared camera employing this type of sensor.
TABLE 1Sample value matrix. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .45.0045.0044.8044.6044.3044.1043.6043.3043.3042.6040.5037.9036.70. . .. . .45.0044.9045.1045.2045.2045.1044.7044.7044.6044.6044.0042.2040.70. . .. . .44.9045.3045.6046.0046.1046.0045.6045.6045.2044.4043.4043.2042.00. . .. . .45.0045.5045.8046.2046.5046.3045.9046.1046.6046.3045.9044.9041.90. . .. . .44.5044.9045.5046.0046.0045.9045.9046.5047.6048.1047.7046.5042.50. . .. . .43.0043.9044.5044.9045.7046.9047.7048.3048.7048.8049.0048.2045.90. . .. . .44.8045.4045.9046.8047.4048.6049.3049.5049.6049.7050.0049.6048.30. . .. . .45.6045.8045.7046.1048.0049.2050.1050.5050.8050.9051.1050.8049.90. . .. . .46.0046.4047.4048.0049.5050.6051.0051.7052.2052.3052.5052.1051.30. . .. . .47.4048.0049.3050.1051.3052.0053.0053.7054.0054.4054.4054.0053.30. . .. . .48.6049.5050.5051.3052.5053.8055.0055.9056.3056.6056.7056.4055.70. . .. . .49.3050.9051.7052.9054.5055.9057.1058.2058.9059.7060.3060.5060.10. . .. . .49.9052.2053.6054.8056.2057.5059.0061.3065.1067.1068.4068.9068.60. . .. . .50.7053.3055.1056.8058.8061.4064.8068.3071.2074.3076.3077.5077.50. . .. . .52.3054.4056.6059.8065.8069.7072.0074.9077.9081.2083.5085.2086.00. . .. . .53.7056.2061.5067.0071.2074.7078.0081.5084.7087.9090.9092.9094.20. . .. . .55.2060.9067.1071.1074.4078.9082.1086.1090.1093.9097.0099.00100.60. . .. . .57.8065.1070.1072.8077.4081.9085.2088.4093.8098.80101.90104.10105.70. . .. . .61.3066.1070.8075.9080.0083.0085.9092.3099.60104.00106.70108.40109.50. . .. . .64.3068.1072.3077.2082.0086.4092.70100.20105.60108.50110.10111.40112.30. . .. . .66.3070.3074.5079.9086.9094.70100.90106.30109.80111.50112.40113.10114.30. . .. . .67.9070.4073.5080.2092.00101.70106.90110.20112.90115.10115.70115.40114.50. . .. . .70.0072.8074.4080.4096.10105.60109.90113.20115.20117.60118.80117.50109.30. . .. . .71.5074.6075.5084.70100.30108.70112.10115.40117.80119.00118.60111.7094.40. . .. . .71.7073.6076.5091.10105.30112.00114.40116.60119.30120.00113.3095.7074.20. . .. . .71.6072.9080.9096.40108.60114.20116.50117.90117.10114.7099.8075.9059.00. . .. . .71.1072.7084.00100.00110.70115.60118.20118.90114.30100.9079.3059.2051.30. . .. . .70.8072.5085.10101.40112.20116.70119.30120.10113.7092.3065.8051.5048.70. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .69.1069.4085.90104.00113.00116.20116.00110.4093.7071.7056.9049.8047.70. . .. . .69.1070.6086.10103.50112.50115.20113.00101.3081.4063.2054.9050.8048.30. . .. . .70.0070.0086.30103.40111.90114.60109.9093.6072.2058.6053.6051.8049.80. . .
This final matrix was obtained and decoded by a calibrated internal firmware or software to correspond to actual temperatures of the aimed at objects. Several correction factors built in the factory and adjusted in the field are included in these values. These processed values are then mounted to form electronic images, contained between the technical camera limits, independent on the camera type or model with which they were produced, and also independent of the observed object type, mechanical, electrical, masonry, plastic, organic, biological, or live organism etc. These built images can be presented in black, white and gray, or converted automatically to a false color scale.
Irrespective of electronic circuitry and internal software used or developed by any manufacturer, the entire infrared information is translated to a visual format that can be recognized by the human eye for neural and cognitive processing. The purpose of usual processing software or firmware applied to these images is to transform this values matrix in different black and white or false color tones that are more or less identifiable by the human eye whereby making the identification of regions of increased or lowered temperatures easier as can be seen in the two mugs shown in FIGS. 4a and 4b.
Another typical commercial software conversion changes the original values matrix or “black and white” images produced by the electronic circuitry and resident software to specific color arrangements producing false color images as shown in FIGS. 5a-c. This is done in order to attempt to build more suitable images for the human retina since its middle region is more capable to see in colors than in black and white due our biological retina cell structure called cones and rods. The result of conventional processing can be seen also in FIGS. 8a, 8b and 8c, and is explained in detail below. However, the final results obtained are poor and analyzing them is tiring to the human eye and brain leading the infrared camera operators to become easily tired and to commit more errors. Such errors lead to large financial losses.
Actually commercially available color coding processes applied on any infrared image lack the precision mixing for many colors and negatively impact the truly important technical information available to the user, mainly when the temperature differences are not so expressive. This happens because the black and white rod and color cones of human retina are not mimicked or emulated by the commercial color arrangements available on the market. The actually commercially available infrared false colored images are saturated with colors and lack precision and discrimination for a comfortable and clear and economic productive diagnosis of infrared image contents.